Fuzzy logic control of telerobot manipulators

Telerobot systems for advanced applications will require manipulators with redundant 'degrees of freedom' (DOF) that are capable of adapting manipulator configurations to avoid obstacles while achieving the user specified goal. Conventional methods for control of manipulators (based on solution of the inverse kinematics) cannot be easily extended to these situations. Fuzzy logic control offers a possible solution to these needs. A current research program at SRI developed a fuzzy logic controller for a redundant, 4 DOF, planar manipulator. The manipulator end point trajectory can be specified by either a computer program (robot mode) or by manual input (teleoperator). The approach used expresses end-point error and the location of manipulator joints as fuzzy variables. Joint motions are determined by a fuzzy rule set without requiring solution of the inverse kinematics. Additional rules for sensor data, obstacle avoidance and preferred manipulator configuration, e.g., 'righty' or 'lefty', are easily accommodated. The procedure used to generate the fuzzy rules can be extended to higher DOF systems

Design, Development And, Psychometric Assessment of an Inventory on Concepts Pertinent to Developing Proficiency in Organic Reaction Mechanisms

This three-phase study was conducted to design, develop, and psychometrically analyze the Reaction Mechanisms Concept Proficiency Inventory (RMCPI). In the first phase, open-ended interviews were conducted with organic chemistry instructors (N=11) to obtain their opinion on concepts pertinent to developing proficiency in organic reaction mechanisms. The results yielded 11 pertinent concepts. Additionally, participants believed that organic reaction mechanisms are essential for mastering organic chemistry and students have difficulty with understanding the meaning and utility of the curved-arrows. The difficulties that students have with reaction mechanisms could be due to a lack of understanding of fundamental general chemistry and organic chemistry concepts. The second phase of this study consisted of a national survey of organic chemistry instructors (N=183) to generalize the results obtained from the first phase. Organic chemistry instructors were asked to rate the importance of the concepts identified in phase 1. The results indicated a general consensus at the national level regarding these concepts and a list of 10 concepts was obtained. Additionally, there was a consensus at the national level regarding the importance of organic reaction mechanisms and the difficulties students face with this important area of organic chemistry education. The third phase of this study consisted of the development of the inventory, test administration, and psychometric analysis. During the development of the inventory, open-ended questions under each of the pertinent concepts identified were administered to first-semester organic chemistry students (N=138) to obtain distractors from their alternate conceptions. Open-ended interviews were conducted with first-semester organic chemistry students (N=22) to obtain information on their thought process while answering the questions and identify additional alternate conceptions. These alternate conceptions were used as distractors for the two-tier items in the inventory. A pilot version, and a beta version of the inventory were administered to 109 and 359 first-semester organic chemistry students respectively. The 26-item alpha version of the RMCPI was administered to 753 first-semester organic chemistry students from 14 different universities across the U.S.A. At the item level, Classical Test Theory and Rasch analysis were used to assess item functioning. At the test level, face validity, content validity, and construct validity using Rasch analysis were utilized to establish the validity of the data obtained using the RMCPI. The reliability of the data obtained using the RMCPI was assessed by computing the Cronbach’s alpha value, and the item and person separation reliability. The results indicate that the items on the alpha version of the RMCPI are functioning well and the instrument is measuring a unidimensional construct which suggests that the RMCPI could be used by organic chemistry instructors as an effective assessment tool to detect students’ alternate conceptions on concepts pertinent to developing proficiency in organic reaction mechanisms. Additionally, the validity and reliability of the data meet the acceptable standards for a concept inventory

Hybrid Approach for Emotion Classification of Audio Conversation Based on Text and Speech Mining

AbstractOne of the greatest challenges in speech technology is estimating the speaker's emotion. Most of the existing approaches concentrate either on audio or text features. In this work, we propose a novel approach for emotion classification of audio conversation based on both speech and text. The novelty in this approach is in the choice of features and the generation of a single feature vector for classification. Our main intention is to increase the accuracy of emotion classification of speech by considering both audio and text features. In this work we use standard methods such as Natural Language Processing, Support Vector Machines, WordNet Affect and SentiWordNet. The dataset for this work have been taken from Semval -2007 and eNTERFACE’05 EMOTION Database

Space biology initiative program definition review. Trade study 1: Automation costs versus crew utilization

A significant emphasis upon automation within the Space Biology Initiative hardware appears justified in order to conserve crew labor and crew training effort. Two generic forms of automation were identified: automation of data and information handling and decision making, and the automation of material handling, transfer, and processing. The use of automatic data acquisition, expert systems, robots, and machine vision will increase the volume of experiments and quality of results. The automation described may also influence efforts to miniaturize and modularize the large array of SBI hardware identified to date. The cost and benefit model developed appears to be a useful guideline for SBI equipment specifiers and designers. Additional refinements would enhance the validity of the model. Two NASA automation pilot programs, 'The Principal Investigator in a Box' and 'Rack Mounted Robots' were investigated and found to be quite appropriate for adaptation to the SBI program. There are other in-house NASA efforts that provide technology that may be appropriate for the SBI program. Important data is believed to exist in advanced medical labs throughout the U.S., Japan, and Europe. The information and data processing in medical analysis equipment is highly automated and future trends reveal continued progress in this area. However, automation of material handling and processing has progressed in a limited manner because the medical labs are not affected by the power and space constraints that Space Station medical equipment is faced with. Therefore, NASA's major emphasis in automation will require a lead effort in the automation of material handling to achieve optimal crew utilization

FocusFlow: Leveraging Focal Depth for Gaze Interaction in Virtual Reality

Current gaze input methods for VR headsets predominantly utilize the gaze ray as a pointing cursor, often neglecting depth information in it. This study introduces FocusFlow, a novel gaze interaction technique that integrates focal depth into gaze input dimensions, facilitating users to actively shift their focus along the depth dimension for interaction. A detection algorithm to identify the user's focal depth is developed. Based on this, a layer-based UI is proposed, which uses focal depth changes to enable layer switch operations, offering an intuitive hands-free selection method. We also designed visual cues to guide users to adjust focal depth accurately and get familiar with the interaction process. Preliminary evaluations demonstrate the system's usability, and several potential applications are discussed. Through FocusFlow, we aim to enrich the input dimensions of gaze interaction, achieving more intuitive and efficient human-computer interactions on headset devices

Livelihood security policy can support ecosystem restoration

Earth faces an unprecedented ecological crisis: the destruction of its ecosystems. Despite increasing interest in restoration, including through the UN Decade on Ecosystem Restoration (Decade), lack of financing and resources mean efforts to reverse degradation have advanced slowly. Restoration efforts require new approaches to ensure the needs of different stakeholders are met. However, analyses of policies and opportunities that help to finance restoration while improving socioecological outcomes, are lacking. This paper analyzes livelihood security funding and opportunities for ecosystem restoration, drawing on India's Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA), the world's largest livelihood security program. The paper analyzes MGNREGA's performance between financial years 2013–2021, focusing on the financing of ecosystem restoration-related works, community mobilization and policy implementation in the early part of the COVID-19 pandemic. Then, the paper reflects on the benefits and shortcomings of MGNREGA and considers wider lessons for the Decade. MGNREGA generated significant funding flows and numbers of projects nationally, which can contribute to ecosystem restoration. Policy design enabled the continuation and increase of works even during the first year of the COVID-19 pandemic. Our findings demonstrate the potential of linking ecosystem restoration with development policies to unlock funds, on a national scale. To maximize contributions to ecosystem restoration nevertheless requires capacity building, inclusion of environmental indicators and integration of best ecosystem restoration practices